One significant challenge faced in the drilling of oil and gas wells is predicting the future drilling performance of a drilling system. There are a number of downhole conditions and/or occurrences which can be of great importance in determining how to proceed with an operation, including selecting drilling devices and operating parameters that will be used in a particular drilling operation.
In many situations multiple wells are drilled within a single field. When drilling a new wellbore within such a field, log data from a nearby “offset” well data is often used to select the drilling equipment and drilling parameter that will be used to drill the new wellbore. This typically involves comparing the performance of drilling devices (typically in terms of average rate of penetration (ROP)) that were used to drill the offset wells. Over the course of the development of the field, drilling device selection and drilling parameter selection gradually improves. This gradual improvement, sometimes referred to as a “learning curve”, is typically slower than desired often requiring drilling ten or more wells to identify optimal drilling devices and drilling parameters. Additionally, the use of overall drilling performance in offset wells may provide spurious inferences where a field has significant lithology, mechanical property, and thickness variations. In such situations, the use of data from an offset well is often an inaccurate indicator of whether a particular drilling device was the best selection for drilling a particular wellbore.
Accordingly, such information is often of limited value in predicting how a particular drilling device or how particular drilling equipment will perform in fields with significant variations in lithology and mechanical properties. Such use of offset well data in fields with variations in lithology often results in the selection of drilling devices and drilling parameters that are not optimized. Such non-optimized selections result in increased drilling times and increased cost.